Abstract

Background:We previously reported the prognostic impact of the number of involved lymph nodes (LNs) on survival in non-small cell lung cancer (NSCLC). However, it remains unknown whether the total number or anatomic location of involved LNs is a superior prognostic factor.

Methods:A total of 689 patients with NSCLC who underwent complete resection involving dissection of the hilar and mediastinal LNs with curative intent of ≥ 10 LNs were enrolled. The association between the total number of LNs (nN) involved and survival was assessed by comparison with the anatomic location of LN involvement (pathologic lymph node [pN]), the present nodal category.

Results:We classified the patients into five categories according to the combined pN and nN status as follows: pN0-nN0, pN1-nN1-3, pN1-nN4−, pN2-nN1-3, and pN2-nN4. Although there was no statistically significant difference between the pN1-nN4− and pN2-nN1-3 categories, pN2-nN1-3 had better prognoses than pN1-nN4−. On multivariate analysis, the nN category was an independent prognostic factor for overall survival and disease-free survival (vs nN4−; the hazard ratios of nN0 and nN1-3 for overall survival were 0.223 and 0.369, respectively, P < .0001 for all), similar to the pN category. We propose a new classification based on a combination of the pN and nN categories: namely, N0 becomes pN0-nN0, the N1 category becomes pN1-nN1-3, the N2a category becomes pN2-nN1-3 + pN1-nN4−, and the N2b category becomes pN2-nN4. Each survival curve was proportional and was well distributed among the curves.

Conclusions:A combined anatomically based pN stage classification and numerically based nN stage classification is a more accurate prognostic determinant in patients with NSCLC, especially in the prognostically heterogeneous pN1 and pN2 cases. Further large-scale international cohort validation analyses are warranted.

Return to: A Proposal for Combination of Total Number and Anatomical Location of Involved Lymph Nodes for Nodal Classification in Non-small Cell Lung Cancer

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